The emergence of drug resistant malaria parasites has been a major hurdle in the control of Plasmodium falciparum, which has evolved resistance to nearly every antimalarial drug in use. A major concern is the apparent emergence of resistance to the current front-line artemisinin derivatives, which could spark a global health crisis. In order to ensure the continued efficacy of these drugs, early detection of resistance, good surveillance, and containment are required. The current clinical tool for phenotyping parasites in the field and monitoring therapeutic efficacy of artemisinins is the parasite clearance curve. Parasites that have longer slower clearance times (longer half-lives) are considered more resistant. Parasite clearance curves are less informative in regions with relatively high complexity of infection. This is because the parasite clearance curve is a whole-infection level measure that represents a weighted average of the clearance phenotypes of different parasites within that sample. In Africa, the majority of falciparum malaria infections are polyclonal meaning that resistant parasites are likely to share their host with sensitive parasites, particularly early during the spread of resistance. In these areas, the effects of resistant clones on infection-level estimates of resistance may therefore be obscured by the sheer number of sensitive parasites in an infection. In order to overcome this limitation, we previously proposed a novel approach that capitalizes on second generation sequencing in order to reveal phenotypic signatures of resistance among individual parasite clones that rise in relative abundance over the course of drug treatment in polyclonal infections. Using these new deep sequencing protocols, we confirmed this hypothesis, finding clones with clearance half-lives similar to artemisinin resistant parasites from Asia among Tanzanian isolates. Thus, emerging artemisinin resistance in Africa might go undetected using the standard clinical definition. None of the resistant clones identified in Tanzania contained polymorphisms in the kelch (K13) gene recently associated with high-level artemisinin resistance in Asia. Accordingly, these resistant clones would even go undetected by molecular surveillance. These findings suggest that clones with low-level resistance to artemisinins exist in Africa and will go undetected until they become dominant in a polyclonal infection. In this proposal, we seek to better characterize these African resistant clones. Our deep sequencing approach provides a novel framework for studying antimalarial resistance at this early stage and potentially the long-term evolution of artemisinin resistance in Africa. We will use it to confirm that slow clearance by these parasite clones is due to resistance rather than other clinical factors. With further investigation of these low frequency slow clearing clones and the functional significance of newly described novel African K13 mutations that may impact resistance, we have the chance to detect resistance prior to significant clinical failures in Africa and understan the ecological factors that may enhance or retard that spread.